Business intelligence (BI) refers to a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help information workers (IWs) make better business decisions. BI applications typically address activities such as decision support systems, querying, reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. A variety of data sources may be accessed to provide input data relevant to the objectives of each BI application.
Discovering the data sources capable of providing this relevant input data can be difficult and time-consuming. First, a developer typically visits Web sites of numerous data source companies to determine which of them, if any, offer the relevant data in a package and at a price that meets the developer's needs. Second, upon identifying the appropriate data sources and data offered thereby, the developer purchases the data via separate transactions with each data source company. Third, the companies may deliver the purchased data to the developer in different formats, e.g., via Web service, Microsoft EXCEL® spreadsheet, a DVD of CSV data, XML data, RSS feeds, etc.
Furthermore, the step of determining whether a data source company offers the relevant data is particularly challenging. While a data source company may offer a directory of data feeds and display samples of the data to the developer (e.g., in a chart), such companies do not typically allow a developer to interact with a particular data feed, especially in combination with his or her own data and business logic, until he or she pays for the access. As such, the customer is unable to do a trial run with the data feed to make sure it provides the right data for a desired objective.
Moreover, providing example data-specific applications to attract prospective subscribers to a particular data feed implies a significant development effort by the data source companies. Yet, such companies are typically more skilled in data collection and provisioning than in significant application development efforts.